Web Design Scraping: Enabling Factors, Opportunities and Research Directions

The number of online users accessing websites and consuming online services via their desktop and mobile browsers is on a constant rise. This paper coins and discusses the concept of web design scraping, which primarily promotes the idea of extracting, understanding, and modeling website components and characteristics and thereby inferring the meaning of the web design. Moreover, web design scraping emphasizes the role of state-of-the-art computing technologies and approaches, especially those powered by machine learning, in consolidating the understanding and intelligent construction and customization of website interfaces. Moreover, this paper discusses several enabling factors for web design scraping and recommends four research directions. The most notable research trends focus on the prediction of user satisfaction towards personalized web designs and the smart revamping of websites automatically by applying machine learning techniques that learn from the interaction history, preferences, and habits of online users.

I. Introduction

The number of website users is on the rise, exceeding 4.54 billion active web viewers worldwide [1]. Moreover, there are approximately 1.72 billion websites accessible through desktops and smartphone devices [2]. However, research studies have reported that, on average, users abandon websites within the first 3 seconds due to diverse reasons, including the complexity and slow loading times of sites [3]. Therefore, developers must produce efficient yet compelling web designs that accommodate the taste of their users and keep up with the technological changes. Furthermore, current websites would need to be responsive to satisfy the enormous variability enforced by modern smartphones concerning screen size, resolution, and supported technologies. In user-centered software engineering, user testing is a vital ongoing activity to ensure that the software artifacts produced conform to the user needs and requirements, thus ensuring the highest levels of software acceptance and adoption by the end-users. However, conducting validation testing with real users is a sophisticated and laborious process that requires significant expertise, resources, and time.